Results 211 to 220 of about 30,043 (263)
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Modified salp swarm algorithm for global optimisation
Neural Computing and Applications, 2021Salp swarm algorithm (SSA) is a newly swarm-based metaheuristic algorithm that simulate the swimming and foraging behaviour of salps in oceans so to search for global optimum solution. Similarly to other metaheuristic algorithms, SSA suffers from poor convergence rate and stagnation in local optima.
Fatima Ouaar, Redouane Boudjemaa
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Quantum mechanics inspired Particle Swarm Optimisation for global optimisation
International Journal of Artificial Intelligence and Soft Computing, 2010This paper presents a novel variant of quantum mechanics inspired Particle Swarm Optimisation (PSO) algorithm named constrained/unconstrained Quantum Particle Swarm Optimisation (CQPSO). The proposed algorithm has the properties of quantum mechanics embedded in the structure of the PSO along with the presence of a quadratic interpolation recombination ...
Radha Thangaraj +3 more
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Memetic Strategies for Global Trajectory Optimisation
2009Some types of space trajectory design problems present highly multimodal, globally non-convex objective functions with a large number of local minima, often nested. This paper proposes some memetic strategies to improve the performance of the basic heuristic of differential evolution when applied to the solution of global trajectory optimisation.
Vasile, Massimiliano, Minisci, Edmondo
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Vine creeping algorithm for global optimisation
2010 Second World Congress on Nature and Biologically Inspired Computing (NaBIC), 2010This paper presents a novel vine creeping optimisation algorithm based on the integration of the Levenberg-Marquardt algorithm into a revised non-revisiting genetic algorithm. The global search of the genetic algorithm is enhanced in efficiency and accuracy by incorporating the Levenberg-Marquardt algorithm into the selection and mutation process.
Christopher Neil Young +2 more
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Global optimisation in neural network training
Neural Computing & Applications, 1997This paper presents a new neural network training scheme for pattern recognition applications. Our training technique is a hybrid scheme which involves, firstly, the use of the efficient BFGS optimisation method for locating minima of the total error function and, secondly, the use of genetic algorithms for finding a global minimum.
Lucas Chi Kwong Hui +2 more
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Modular global optimisation in chemical engineering
Journal of Global Optimization, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
S. Balendra, Ian David Lockhart Bogle
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Hesitant adaptive search for global optimisation
Mathematical Programming, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
David W. Bulger, Graham R. Wood
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Numerica A -- Modeling Language for Global Optimisation
Journal of the Operational Research Society, 1998(1998). Numerica A Modeling Language for Global Optimisation. Journal of the Operational Research Society: Vol. 49, No. 11, pp. 1228-1228.
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Global Optimisation of Nonconvex MINLPs
Computers & Chemical Engineering, 1997Abstract The recent advances in mathematical programming approaches applied to process design and operation problems have produced a need for the ability to find the global optimum of a nonconvex problem containing discrete variables (a nonconvex MINLP). This paper presents a modified version of the reformulation/spatial branch-and-bound algorithm of
Edward M.B. Smith +1 more
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Artificial Orca Optimiser: Theory and Applications for Global Optimisation Problems
Expert SystemsABSTRACTWith the growing complexity of real‐world engineering optimisation problems, interest in meta‐heuristic algorithms is increasing. However, existing meta‐heuristic algorithms still suffer from several shortcomings, including a poor balance between global and local search, a tendency to converge toward the centre of the solution space, and ...
Lin Wang 0001, Xuerui Wang, Yingying Pi
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